University Of California Berkeley

NSF Awards · FY 2024 · 2024-09

Over the last decade, K-12 science education has seen the development and surge in comprehensive high-quality instructional materials designed to address standards aligned with the Framework for K-12 Science Education. Meanwhile, localization—organizing instruction around local phenomena and incorporating students’ social, cultural, and linguistic resources—has been proposed as a way to better connect science instruction to students’ interests and the priorities of their local communities. Both localization and high-quality instructional materials have been found to support equitable learning opportunities and outcomes in K-12 science education. However, there are many unresolved questions in science education about how to best leverage the advantages of localization in the context of high-quality instructional materials, which are typically developed at a national scale. This project will support a conference series, including an in-person gathering and virtual follow-up meetings, that will bring together teachers, researchers, education leaders, and instructional material designers to investigate these questions. Participants will come together to build a shared understanding of how to integrate the use of high-quality instructional materials with the benefits of localizing these materials to better address students’ contexts and backgrounds. By fostering dialogue, sharing models, and setting priorities for future research and design, the project seeks to build knowledge about inclusive, effective and culturally responsive approaches to science instruction that will advance equitable science education in K–12 classrooms. This one-year conference project primarily focuses on the promise and challenges involved in integrating localization with comprehensive high-quality instructional materials to enhance equitable learning outcomes in K-12 science education. The project will organize an in-person conference followed by a series of four follow-up virtual meetings involving a diverse group of fifty participants, including teachers, district leaders, state education agency leaders, researchers, and instructional materials designers. Methods will include collaborative discussions, presentations of existing models, and evidence-based analyses to clarify definitions and identify priorities for future research and design efforts. The outcomes will be a proposed research and design agenda for the localization of high-quality instructional materials, along with practical examples and models of current approaches. These outcomes will be disseminated beyond the conference, targeting practitioners, designers, and researchers through co-authored conference presentations and publications, as well as shared via teacher social media, newsletters, and professional learning communities. By addressing the inherent tension between national-scale usability of high-quality instructional materials and the need for culturally and locally relevant instruction, this project aims to spur innovation and contribute to the development of truly equitable science instructional materials, ultimately advancing the field of science education. The Discovery Research preK-12 program (DRK-12) seeks to significantly enhance the learning and teaching of science, technology, engineering and mathematics (STEM) by preK-12 students and teachers, through research and development of innovative resources, models and tools. Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for proposed projects. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

The modern oceans and the ecosystems they contain resulted from millions of years of change in physical and biological ocean systems. One aspect of the environment that has a large impact on marine animals is the amount of available food and nutrients. Understanding how individual organisms and biological communities adapt and respond to changes in nutrient availability advances scientific knowledge by 1) improving understanding of how the physical environment drives evolution, and 2) providing insight into how decreased nutrients might trigger regional extinction events. These results are important for understanding the geologic history of life as well as its future. In addition to these scientific objectives, this project supports the training and advancement of students through 1) an inclusive field course for advanced undergraduate students, 2) the development of a graduate student cohort trained to participate in international field research, and 3) the production of a bilingual graphic novel to increase scientific literacy in K-12 students in the US and the Caribbean. The goal of this project is to understand and characterize the relationship between surface productivity and ecological structure in marine benthos by (1) evaluating how productivity affects the energetic and trophic structure of marine benthic communities on both sides of the modern Isthmus of Panama, (2) using this knowledge to evaluate the fossil record of Caribbean benthic ecosystems before, during, and after the uplift of the isthmus, and (3) relating ecosystem changes driven by productivity shifts to the well-documented Caribbean extinction event ~2 Ma. The project leverages collections from the Panama Paleontology Project, which includes extensive collections of modern mollusks and rich fossil collections, to meet these objectives. The project applies new technologies, including high-throughput imaging and automated morphometric methods, to analyze the size-frequency distribution and calculate measures of energetics. The project also explores how trophic composition, larval dispersal mode, and predatory attack frequencies in mollusk shells in modern death assemblages and fossil assemblages vary across productivity gradients. The project will advance the community’s current understanding of how these ecological traits are influenced by productivity in modern systems and the role they have played in the evolution of modern Caribbean ecosystems. The Biological Oceanography Program co-reviewed and co-funded this project with the Sedimentary Geology and Paleobiology Program. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-09

UC Berkeley Training HealthEquity ScholaRs in InnoVation, PrEvention, and Social Impact (UCB-THRIVES) Fellowship Program Despite extensive research documenting the existence of pervasive health inequities over the lifespan, there is little research on preventive interventions to address these inequities. Thus, there is an urgent need to train the next generation of public health professionals, especially those from historically marginalized backgrounds, to be equipped with a comprehensive toolkit to confront these challenges. The UC Berkeley Training HealthEquity ScholaRs in InnoVation, PrEvention, and Social Impact (UCB-THRIVES) T32 Fellowship Program proposes a collaboration between three graduate groups in the School of Public Health (UCB-SPH): Epidemiology, Health Policy, and Environmental Health Sciences. The overarching objective is to equip the upcoming generation of health equity scholars with the structural competency and methodological acumen required to develop and evaluate multi-level, preventive interventions to address health equity in partnership with marginalized communities. UCB-SPH is uniquely positioned to provide this training due to its pioneering leadership in social epidemiology, community-engaged research, and advanced statistical methods in causal inference. Furthermore, UCB-SPH demonstrates a profound commitment to diversity, equity, inclusion, belonging, and justice, which will be leveraged to create a rich training environment for pre-doctoral students. T32 trainees will receive innovative classroom training in health equity, multi-level interventions, and methods in multi-level preventive interventions through coursework and immersive research experiences, and they will be guided throughout by Individual Development Plans. The core training domains will be supplemented with three salient cross-cutting themes critical to achieving health equity: 1) community engagement, 2) anti-racism, and 3) social impact. The UCB-THRIVES T32 Program has an excellent leadership team with Drs. Mujahid and Fernald serving as Co-Directors, bringing a formidable track record of mentorship and complementary expertise to ensure the academic and career success of the UCB-THRIVES trainees. The UCB-THRIVES T32 Fellowship Program unites a cohort of 35 faculty mentors, including 65% female-identified faculty, 40% under-represented minority faculty, and 31% at early career stages. Furthermore, the program faculty have a strong record of grant funding, mentorship, and trainee success and will contribute their content area expertise and opportunities to acquire practical research experience in community-based settings. An Advisory Committee was thoughtfully selected to provide additional input and includes internationally recognized experts in health equity, anti-racism, multi-level community-engaged preventive interventions, community-engaged research, robust methodologies, and social impact. Ultimately, the UCB-THRIVES T32 Program will help foster a new generation of scholars poised to pioneer innovative, preventive solutions to the most pressing health equity challenges, all while embracing social justice as a guiding principle.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY In the US, disparities between non-Hispanic Black and White patients in pregnancy-related outcomes, including perinatal depression symptomology, are stark and pervasive. Depression symptoms, which can result from social stress, including racism-related stress, contribute to racial and ethnic disparities in pregnancy-related outcomes. Interventions that buffer against social stress, including racism-related stress, in perinatal care have potential to reduce racial and ethnic disparities in postpartum depression symptomology. Patient-centered care and social support are key components for addressing racism-related stress in the healthcare setting. However, to our knowledge, there are no interventions for prevention and treatment of postpartum depression symptoms for Black birthing people that are delivered in perinatal care and explicitly promote patient-centered care and provide social supports. The proposed project engages Beloved Birth Black Centering (BBBC) program in generating evidence to improve perinatal care interventions that address racism-related stress using a community-engaged model of perinatal health services created by and for Black birthing people. BBBC incorporates five evidence- based practices (EBPs): racially concordant care, midwifery-led group perinatal visits, doula support, wrap- around care, and culturally aligned black birthing education. Through these bundled EBPs, BBBC promotes patient autonomy, respectful interactions, social connection, and connection to community resources – all of which have the potential to reduce postpartum depression symptoms. We will employ a pragmatic trial using a mixed-methods analytic approach to analyze secondary, longitudinal data from electronic health records (EHRs) and patient surveys. The overall objective of the proposed research is to test a bundled perinatal care intervention on postpartum depression symptomology and explore mechanisms by which postpartum depression symptoms can be prevented and treated among Black birthing people. This research proposal’s overall objective aligns with the NIMHDs’ 2021-2025 strategic goal 3: “Develop and test interventions to reduce health disparities”. Aim 1 will estimate the association of between BBBC and postpartum depression symptoms among Black birthing people and will use propensity score analyses to compare postpartum depression symptoms among patients who received perinatal care through BBBC (treatment group) to those receiving routine perinatal care (comparison group). Aim 2 will assess the extent to which patient autonomy in decision-making and respectful clinician-patient interactions in perinatal care is associated with postpartum depression symptoms among BBBC participants using data from EHRs and patient surveys. Aim 3 will explore how BBBC patient experiences of perinatal care may impact postpartum depression symptoms using data from patient surveys. This work is responsive to the growing evidence showing that racism-related stress impacts health, and will ultimately advance the science of health disparities research.

NSF Awards · FY 2024 · 2024-08

A postcard image of rain clouds on the upwind slope of a mountain, with the summit rising above the clouds, is a traditional starting point for thinking about how mountains generate precipitation. The image captures an important mechanism for orographic precipitation in the middle latitudes: the mountain blocks the prevailing wind, forcing rising motion in stable air which produce clouds thick enough to make rain but often too shallow to obscure the summit. But there are other ways that mountains can generate precipitation, particularly in the tropics and in cases where the air is only marginally stable to convection. For example the Western Ghats of India produce rain by blocking the wind blowing across the Arabian Sea during the summer monsoon, but instead of shallow clouds the mountains produce convective towers that are several times higher than the mountain tops. Moreover, the orographic precipitation is not confined to the mountain slopes, extending considerably upwind into the Arabian Sea. The Principal Investigator (PI) of this award has developed a simple theory for convective orographic precipitation in which the airflow over the mountain produces gravity waves which in turn trigger convection. The convection is caused by variations in lower-tropospheric buoyancy associated with the waves, rather than condensational cooling in stable air forced upslope, thus rainfall can occur in air that has not yet reached the mountain. Work under this award further develops the theory of tropical orographic precipitation with the goal of understanding its sensitivity to large-scale environmental factors including mean wind speed, temperature, and humidity. The work seeks to determine how tropical orographic precipitation responds to the variability associated with El Nino events and other modes of climate variability and to the long-term warming of the tropics due to greenhouse gas increases. In addition to the PI's recent work on convective orographic precipitation the project incorporates a previously developed theory for overturning circulations due to surface heating over mountains and a theory for the strength of convective updrafts derived from Carnot cycle efficiency. The work takes advantage of observations from multiple field campaigns and satellite missions as well as a variety of model simulations. Among these are simulations with the Weather Research and Forecasting model (WRF) in realistic and idealized configurations, many of which involve a rectangular domain with a north-south mountain ridge in the middle, the Large Ensemble of simulations from the Community Earth System Model (CESM-LE), and simulations from the Coupled Model Intercomparison Project (CMIP). The work is of societal as well as scientific interest given the prevalence of orographic precipitation in the tropics and the lack of even rough estimates for how much its intensity is likely to change as the world warms. The project connects to real-world orographic precipitation through the installation of two weather stations in a mountainous region of Cameroon, where the PI advises a group of cooperative farmers. Observations from the weather stations are incorporated into the PI's undergraduate class on weather and climate. In addition, the project provides support and training to a graduate student, thereby providing for the future workforce in this research area. The project also supports two undergraduate interns in each summer, recruited through the UC Berkeley Undergraduate Research Apprenticeship Program. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-08

With the support of the Chemical Synthesis program in the Division of Chemistry, Professor Richmond Sarpong of the University of California–Berkeley will study the conversion of one group of compounds that contain a six-membered benzene ring to another group of compounds that contain a seven-membered ring (tropone). This ring expansion protocol will connect two families of compounds that are found in a range of agrochemically and medicinally relevant compounds. The work will expand the scope of seven-membered ring containing compounds in the tropone family and will also provide a platform for training researchers in the practice of multi-step chemical synthesis which will prepare them for positions in the pharmaceutical and agrochemical industries. This work will provide valuable training to a diverse group of graduate students for careers in STEM. The PI is also actively involved in outreach activities in the local community. The goal of the proposed project is to develop a two-step sequence for the conversion of phenols to tropones. Specifically, the intellectual advance is to convert phenols to para-quinols using an oxidative dearomatization reaction. The resulting para-quinols will then be engaged with diazo compounds to effect a net one carbon insertion/ring expansion through what is known as a Büchner–Curtius–Schlotterbeck reaction. A range of Lewis acids and diazo compounds will be investigated to identify reagents and conditions that lead to the highest selectivities and yields. Mechanistic and computational studies will be conducted to gain insight into the selectivity-determining factors so that a broad range of highly selective reactions can be achieved. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-08

IMPRINT for ADRD will consist of two key tracks, combining immersion in the lived experiences of people affected by Alzheimer’s with training in key aspects of entrepreneurship. Specifically, the course will include lessons on key elements of biology and pathophysiology, as well as the social & lifestyle determinants that impact an ADRD patient’s health. It will include an exploration of novel design solutions, such as a digital phenotyping, as well as data science tools to elucidate options for earlier detection and prevention. In addition, participants will observe and potentially engage with patients in their care environments through in-field ethnography. Entrepreneurship training will provide an immersive, inductive learning approach to guide participants and teams on the path from ideation to market, including how to define a problem, methodical approach to solution development. Together, these two tracks combine a patient-centric, technical, and ethical methods that will help participants develop effective, inclusive and comprehensive evidence-based interventions and/or treatments to enhance outcomes for people affected by Alzheimer’s and related dementia diseases. The program will be built on best practices for healthcare-related innovation and entrepreneurship. Key components of the program will be led by academic and industry experts in Alzheimer’s and related dementias, clinical development and evaluation, FDA, legal and regulatory issues, entrepreneurship, SBIR/STTR grant writing, and more. We will collaborate with colleagues and programs from UC Berkeley, UC San Francisco, industry, foundations, memory care centers, and other relevant stakeholders and/or partners. The pedagogical approach will combine project based learning to foster discovery of solutions with adult social learning theory (e,g, cooperative learning, building on each subsequent activity, reinforced by in-field interactions with senior care centers and health technology companies. Program participants will comprise a cohort of 12-15 graduate students and postdocs from diverse backgrounds, disciplines, and interests, with a focus on attracting applicants from underrepresented communities. The IMPRINT program is a one-year, hybrid model, with 15 days of immersive interactive (~12 days at course launch and 5 days at the end) that will cover team building, site visits, prototyping sessions, and final presentations, combined with weekly remote sessions (2 hrs/session x 2 sessions/week). Participants will receive a Certificate in Entrepreneurship & Technology in ADRD upon completion.

NIH Research Projects · FY 2026 · 2024-08

PROJECT SUMMARY Prefrontal cortex (PFC) is a large and heterogeneous brain area comprising the front third of the human brain that has been implicated in numerous mental health disorders. One of the least-studied subregions of PFC is anterior lateral PFC (aLPFC). This region, whose functioning is impacted in disorders like schizophrenia, has been implicated in reasoning, multi-tasking, planning, memory monitoring, decision-making, and more. It behooves us to reach a mechanistic understanding of the fundamental processes subserved by this region; however, there are numerous challenges, including the absence of a precise animal model, inconsistencies regarding terminology and anatomical boundaries, lack of attention to individual variability in anatomy, lack of high-resolution imaging in living participants, and limited evaluation of the generalizability of its function. In response to these challenges, we seek to do a deep dive on its anatomy and function at the individual level in neurotypical adults, using cutting-edge MRI technology. Leading theories presuppose that aLPFC has a domain-general function, processing abstracted representations that are far removed from initial inputs to the brain. However, this assumption has yet to be carefully tested. Here, we capitalize on a body of work implicating a portion of aLPFC in relational reasoning, or the ability to reason about information by jointly consider several sets of mental representations. First, we seek to evaluate the claim of domain-generality by assessing aLPFC's activation and interactions with other brain regions during performance of four relational reasoning tasks; these tasks involve both visual and—for the first time—auditory domains, as well as visuospatial and semantic (or "where" and "what") stimuli processed by different posterior brain regions. Second, to better localize aLPFC activation during reasoning at the single subject level, we seek to assess whether small sulci (grooves) serve as functional landmarks, predicting the location of this functionally defined region. Third, we seek to leverage the exquisite spatial resolution of our NexGen 7 Tesla MR scanner and a combination of two fMRI methods to test whether aLPFC activation during reasoning is predominantly localized to superficial cortical layers, consistent with involvement in local recurrent connectivity that supports integration of high-level mental representations. Fourth, theories of PFC organization either presuppose that aLPFC receives inputs exclusively from other PFC regions or that it also has long-range connections to more domain- sensitive regions in parietal and temporal cortices. Thus, we seek to use high-resolution diffusion-weighted imaging at 7 Tesla to shed light on the provenance of inputs to aLPFC. With strong expertise in PFC function, neuroanatomy, high-field MR imaging technology, and MRI analytic approaches, our team is poised to yield novel insights about PFC function. This study is both theoretically and technologically innovative and will yield a valuable shared dataset. Better characterizing aLPFC structure and function could yield insights for early identification of disordered thinking in neurodevelopmental conditions such as schizophrenia.

NIH Research Projects · FY 2025 · 2024-08

Project Summary The study of the genetic basis of craniofacial adaptations in naturally divergent groups of species can provide an opportunity to uncover novel gene networks and genome regulatory elements with clinical relevance. One of the most remarkable examples of craniofacial diversification across vertebrates is represented in teleost fishes, often associated with their diverse and highly specialized modes of feeding. In my early postdoctoral career, I leveraged a recently established evolutionary model of Cyprinodon pupfishes and established it as a new model system in eco-evo-devo1. This radiation is endemic to San Salvador Island (SSI), and includes a generalist pupfish (Cyprinodon variegatus), and two trophic specialists, the scale-eater C. desquamator, with longer oral jaws, increased oral tooth number, and larger mandibular muscles and the molluscivore, C. brontotheroides, with a shorter jaw with and a novel maxillary extension. Only a few mutations are found to be fixed between specialists2, with almost all of them found in regulatory or intronic regions, suggesting that the genetic changes underlying SSI pupfish craniofacial divergence lie in regions of the genome that affect gene expression control. I hypothesize that temporal and spatial changes in the expression of novel craniofacial candidate genes within the specialist’s gene regulatory networks (i.e., gba3, pycr3, or galr2a) are caused by dynamics differences in the chromatin state of their regulatory regions during development, which in turns, underpins the divergent craniofacial morphological development observed in SSI pupfishes. To test this, I will combine tissue-specific differential expression analysis (Aim 1) with genome-wide studies of chromatin accessibility (Aim 2) in three developmental stages (embryonic pharyngula, hatched larvae, and metamorphic fry) from divergent and non-divergent tissues among SSI pupfish species (oral jaws vs. tail caudal region). In Aim 1, I will identify tissue-specific and specialist-specific spatiotemporal gene regulatory networks (GRNs) by analyzing tissue-specific differential gene expression (DGE) (Aim 1.1) and alternative splicing identification (Aim 1.2) between SSI pupfish’s transcriptomes, life stages, and tissues. In Aim 2, I will explore chromatin state dynamics by analyzing tissue-specific chromatin accessibility (ATAC-seq) across SSI species, life stages, and tissues. I will integrate the spatiotemporal dynamics of DGE and alternative splice variants with chromatin accessibility analyses to build a predictive model to identify and test novel craniofacial gene networks and regulatory regions crucial for pupfish craniofacial divergence (Aim 3.1). The top 5 novel craniofacial candidate genes within the inferred GRN and with paired differences in chromatin accessibility will be tested using HCR (Aim 3.1), CRISPR-Cas9 gene editing (Aim 3.2), and Tol2 transgenesis (Aim 3.3). This study will reveal the different levels of genome regulation governing the evolution and development of craniofacial divergence, opening new avenues of research to understand the genomic basis of craniofacial specialization with potential implications for human craniofacial variation and disease.

NSF Awards · FY 2024 · 2024-08

Gene flow from archaic hominins, Neanderthals and Denisovans, into the ancestors of modern humans has shaped genetic and phenotypic variation in modern humans. Regions of archaic ancestry also provide a unique window into past genomic variation and mutation patterns at deep timescales in human evolution. To date, there are only four high coverage archaic genomes sequenced: three of Neanderthals and one Denisovan, thus, our knowledge of the evolutionary history and role of archaic ancestry in humans remains incomplete. This project will develop novel methods to characterize archaic ancestry in modern humans that do not rely on sequenced archaic genomes. We will apply these methods to whole genome sequences from individuals worldwide for whom we also have rich phenotype data, including previously underrepresented groups from South Asia, Africa, and the Americas. This research will be integrated with an education plan including multiple activities intended to expand quantitative biology training to undergraduate and graduate students, including programming, hands-on genomic data analysis and research internships. This project will develop novel statistical methods to characterize archaic introgression and apply it to large-scale cohorts to learn about the legacy of archaic ancestry in modern humans. Specifically, the project will (1) characterize the evolutionary history and legacy of archaic ancestry in non-African populations, (2) build a novel method to characterize the landscape of archaic ancestry in Africans, and (3) leverage the footprints of archaic ancestry to learn about changes in germline mutation rate during human evolution. Our analysis will generate the largest catalog of archaic ancestry segments and help characterize the role of archaic ancestry in shaping complex traits and evolutionary processes in modern humans. Software developed and data analyzed in publications resulting from the research will be made available to the public on the lab's data repository (https://moorjanilab.org/software/) and through github (https://github.com/MoorjaniLab). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-08

This project will facilitate development of new tools to study mathematical questions related to how physical systems evolve in time. A state of the system corresponds to a point in an even dimensional phase space, and the system evolves along an odd dimensional energy level in the phase space. A particular focus will be placed on understanding the existence and properties of periodic orbits, which describe behavior that repeats in time, especially in the case when the phase space is four dimensional and the energy level is three dimensional. The geometry of the phase space will also be studied, developing methods to determine when one dynamical system is equivalent to another one by a change of coordinates. Various research projects on these topics will provide research training for graduate students in the latest techniques in symplectic geometry and related areas of mathematics. The PI will also engage in multiple outreach activities. Specific projects include the following. Filtrations on embedded contact homology will be studied with the goal of proving in full generality that every contact form on a closed three-manifold has either two or infinitely many simple Reeb orbits. Knot filtered embedded contact homology will be studied with applications to symplectic cobordisms between transverse knots. Symplectic invariants of open domains arising from barcodes in equivariant symplectic homology will be used to classify some open domains up to symplectomorphism. Closing lemmas will be extended to more general vector fields than Reeb vector fields in three dimensions. Universal quantitative invariants will be developed with applications to symplectic embedding problems, constraints on Lagrangian submanifolds, refinements of the Arnold chord conjecture, elementary spectral invariants of contact manifolds, and comparisons between symplectic capacities. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2024 · 2024-08

Project Summary/Abstract The correct implementation of developmental programs depends on information encoded in an organism’s DNA. Despite decades of work in dissecting the spatial control of gene expression in embryonic development, we know relatively little about the temporal control of these programs—largely due to reliance on dead, fixed tissues. Recently, our lab established new technologies for real-time measurements of input transcription factor concentration dynamics and output transcriptional activity in single cells of the early embryo of the fruit fly Drosophila melanogaster. These measurements have revealed that the transcriptional activity of individual genes is not constant in time; rather, bursts of gene expression arise when promoters transition between ON and OFF states. Transcriptional bursting in eukaryotes, particularly in developmental genes, is ubiquitous; most transcription factors control mRNA levels by modulating bursting frequency, duration or amplitude, or some combination thereof. Critically, while we have uncovered which bursting parameters transcription factors modulate to dictate transcriptional dynamics, we remain ignorant about how this control is implemented at the molecular level. Here, we propose to make progress toward uncovering the molecular mechanisms by which the Dorsal activator controls transcriptional bursting in the early embryo of the fruit fly Drosophila melanogaster. We will combine our cutting-edge imaging and computational technologies for simultaneously measuring Dorsal concentration dynamics and the instantaneous state of its target promoters (ON or OFF) in individual nuclei of living embryos. Specifically, we will (1) use our novel compound-state Hidden Markov model to determine whether Dorsal controls burst size, frequency, amplitude, or some combination thereof, in order to generate hypotheses about the mechanisms of action of this activator, (2) determine whether stable clusters of high Dorsal concentration that we recently discovered play an active role in regulating transcriptional dynamics, and (3) use cutting-edge lattice light-sheet and adaptive optics microscopy to detect functional Dorsal binding events at snail and determine how this binding triggers the cascade of biochemical events that leads to the initiation and maintenance of transcription. Overall, our proposed work will establish a clear workflow for the in vivo dissection of the molecular mechanisms of transcriptional control in development. This approach is amenable to implementation in other genes in the fruit fly as well as in other workhorses of developmental biology. We envision that our mechanistic insights will make it possible to derive theoretical models of developmental decision-making that will empower future synthetic applications as well as reengineering of multicellular organisms, for example to fix developmental defects or to halt states of unchecked cellular proliferation in cancer.

NSF Awards · FY 2024 · 2024-08

Non-Technical Abstract Amorphous materials, also known as glasses, lack structural order, making it difficult to calculate and predict their properties compared to crystalline materials which consist of repeated patterns of atoms. This lack of order, however, does not preclude the applicability or scientific impact of amorphous materials; plastics, silicate glasses, and amorphous silicon photovoltaics are examples pertinent to daily life, industry, and technologies, and superconducting amorphous materials changed how we understand superconductivity. Intriguingly, there exists the notion of an "ideal glass", which while remaining disordered, lacks imperfections in that disorder and thus approaches the uniqueness of a crystal, including reproducibility and predictability of its properties. While glasses are traditionally made by liquid quenching, in recent years materials made as thin films by vapor deposition can, under select circumstances, come closer to the ideal glass state than any liquid quenched material. This result is important to understand both because it reveals a hidden order within the structural disorder of a glass and because these glasses without imperfections have properties that are more desirable than the traditional glass. The project will fabricate and measure a class of semiconductor alloys known as chalcogenides that are important to several technologies particularly opto-electronic switches and memories, and potentially for superconducting qubits and coatings for gravitational wave detectors. By varying their composition and growth conditions and studying their structure and properties, the research team will determine how the degree of order affects the properties. The research enables understanding and control of the properties of technologically important amorphous materials and increases our understanding of the fundamental science of amorphous materials, which remains elusive despite decades of study. The project also educates and trains students and helps to increase diversity participation in science; the principal investigator and her students actively engage in efforts to make physics accessible to underrepresented STEM ethnic and socioeconomic minorities. Technical Abstract Researchers prepare and study the structure and tunneling two-level states (TLS) of amorphous chalcogenide alloys with a designed range of compositions grown by physical vapor deposition at temperatures below but near their respective glass transition temperatures under conditions that cause them to lie on a range of thermodynamic and kinetic stability, reflecting a range of enthalpy and entropy. The alloys are phase change materials important to technology including opto-electronic switches and memories, and potentially superconducting qubits and gravitational wave detector mirror coatings. Recent experiments suggest that two extremely different vapor deposited materials (indomethacin and silicon) can form ultrastable glasses with enthalpy near the corresponding crystal and with a low density of TLS, suggestive that these materials are close to ideal glasses, in which the entropy of the glass is very close to that of a crystal, indicating hidden order within their disorder. The research tests the hypothesis that low TLS is achieved by vapor deposition when growth is done near the Kauzmann temperature TK, at which the ideal glass is theoretically produced, if there is sufficient surface atomic mobility at that temperature. The distinction between fragile and strong glass formers is hypothesized to be critical: TK is high for fragile glasses, meaning that high surface mobility is likely near TK, so they grow in a low entropy, near-ideal state, whereas for strong glasses, the opposite is true. The chalcogenides range from fragile to strong as a function of composition, enabling testing of these hypotheses and creation of near-ideal low TLS glasses, providing insight into the intriguing ideal glass state. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-08

AI entered a new and accelerated phase with the public rollout in Nov. 2022, of the generative AI large language model (LLM) ChatGPT, which is a transformer deep learning (DL) model with 1.5 billion parameters trained on 570GB of data. The potential impact of ChatGPT and other chatbots in scientific research, teaching, medicine, government, business, and society at large is enormous. Currently, the dominant empirical paradigm for solving tasks using deep learning is to first pretrain massive models in an unsupervised manner on large data corpora and then fine-tune them on specific tasks of interest. For example, the standard practice for pretraining modern LLMs like ChatGPT is to train models to predict the next token on datasets scraped from the internet, which allows the model to learn meaningful and general representations about language. Although models learn extensively about language during the pre-training phase, they are typically not immediately useful for tasks of interest, and transfer learning must be applied by fine-tuning on a specific downstream task, such as coding, math, chat-botting, etc. There are many important questions about this fine-tuning process, such as how the hyperparameters should be set and when different algorithms can be expected to generalize well. In this project, a theoretical study will be taken to address different aspects of finetuning and transfer learning with the aim of producing practically relevant guidance for improving efficiency and generalization performance for these settings. This project includes financial support and mentorship for graduate students. Concretely, the proposed research will focus on the following two directions: developing methods that help choose the learning rate and rank in a near-optimal manner for a popular finetuning method known as Low Rank Adapters (LoRA). Insights from the large width scaling theory of neural networks will be used to guide how to select hyperparameters appropriately. Successful methods have the potential to greatly reduce the computing cost of hyperparameter tuning when finetuning large models. The second thrust involves studying transfer learning in the context of over-parametrized linear regression. The setting in over-parametrized linear regression is rich enough to provide conceptual insights into modern deep learning yet simplified enough for a rigorous mathematical study of generalization performance. Building upon previous works analyzing in-distribution generalization performance in over-parametrized linear regression and using similar random matrix theoretic tools, extensions will be made to the out-of-distribution transfer learning setting. By rigorously characterizing how transfer learning affects generalization, intuition will be provided for practitioners seeking to predict how various shifts will affect the performance of their models. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-08

This goal of this research project is to investigate little-understood mechanisms that lead to many severe injuries during earthquakes to support the development of new, effective interventions to reduce seismic risks. Through the research, this project aims to utilize new engineering models to capture the critical injury mechanisms and interactions between humans and infrastructure during earthquakes at fine scales in space and time, focusing on predicting earthquake impacts on health and life. This research has the potential to inform policymaking to design effective hard and soft interventions to protect many communities living in vulnerable buildings close to active seismic areas, like in Los Angeles or the Bay Area, California. In addition, the project offers opportunities for PhD training in interdisciplinary methods in engineering and disaster medicine and a broad dissemination of results to scientists and policymakers. The project embraces equity, diversity, belonging, and inclusion in the research design, recruitment of students, training, and teaching plan. This research project integrates civil engineering and disaster medicine concepts, measures, and methods to develop next-generation earthquake casualty models that are more fine-grained and accurate. The novel measures and models will support the design and assessment of novel interventions to reduce risks to health and life. First, the project augments the spatiotemporal granularity of traditionally coarse damage assessments of infrastructure failures to reflect more types of physical mechanisms that lead to earthquake injuries. This part of the project employs both numerical experiments and empirical damage observations of structural and non-structural components. Second, the research elevates the granularity of earthquake injury modeling to predict medical diagnoses and needs rather than just severities, building on a new, more refined taxonomy of earthquake injuries. This part of the project will employ two validated methods to collect granular injury data from experts and field investigations in communities affected by the 2023 Turkey Earthquake. Third, the project will include creation of a hyper-resolution agent-based model coupled with a building dynamics model to explore the effectiveness of hard (e.g., building retrofits) and soft (e.g., earthquake early warning) interventions to reduce injury risks for diverse buildings and populations. Overall, this research distills technical insights for seismic risk reduction, focusing on health and life. The findings will yield insights relevant to communities residing and working in non-ductile concrete frame buildings in the Bay Area, California. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-08

Stents are mesh-like tubes which hold blood vessels and air passages open. There are many types of stents, including bare metal stents, drug eluting stents (DES), airway stents, and stents that anchor bioartifical heart valves in transcatheter (aortic) valve replacement procedures. DES is a metallic mesh platform coated with an anti-inflammatory pharmacologic agent (drug) to reduce re-blocking (restenosis) of coronary arteries and allow normal blood supply to the heart muscle. Implantation of DES continues to be the method of choice in the treatment of patients with symptomatic coronary artery disease. The FDA first approved the use of 3D-printed airway stents in 2020. With the rapid development of 3D printing technology, it is only a matter of time until 3D printed vascular stent are slated for FDA approval. This is what makes this research pressing and timely. This project aims to deliver a comprehensive unified mathematical and computational framework for optimal stent design, producing digital stents ready for 3D printing, tailored to specific uses and patient geometries. In addition to developing novel mathematical and computational approaches, which will influence the field of mathematics, this project will produce tools for designing patient-specific digital stents. Furthermore, it will provide a platform for interdisciplinary mentoring of students and postdoctoral researchers by the main investigators, who include a mathematician, an engineer, and an interventional cardiologist. The mathematical framework to be developed in this project, consists of three modules: 1. A reduced model optimization module for optimal design of mesh-like structures. This stent optimization algorithm outperforms classical engineering and ad hoc optimization approaches in terms of speed and accuracy, since it relies on sophisticated mathematical approaches rooted in dimension reduction modeling and optimization. This is the first stent optimization model (and a computational scheme) that is based on reduced, 1D network modeling of stents. A comparison with a Genetic Algorithm, Proper Orthogonal Decomposition, and Deep Autoencoder Neural Networks approaches will be performed. The stent prototypes will be 3D printed and mechanically tested in a Biomechanics Lab at Berkeley. Medical oversight will be provided by an interventional cardiologist. 2. A fluid-stent-poroelastic structure interaction module simulating the interaction between the blood flow and artery wall with implanted stent, where the arterial walls are modeled as poroelastic solids consisting of two layers: a thin reticular shell layer modeling the intimal layer of arterial walls, and a thick hyperelastic layer modeling the media-adventitia complex. This is the first fluid-structure interaction model that accounts for the multi-layered poroelastic structure of arterial walls, and it includes an implanted stent. A novel partitioned scheme to solve this problem will be developed. 3. A nonlinear advection-reaction-diffusion module simulating drug transport within the vascular wall and in the vascular lumen capturing the pharmacokinetics and advection, reaction, and diffusion processes of anti-inflammatory agents used to coat DES. The models are defined on moving domains. They utilize the advection velocity and the moving domain location calculated in Step 2 above. A monolithic computational scheme will be developed to solve the problem. This module is particularly relevant for the analysis of the performance of drug eluting stents. An integral part of the project will be interdisciplinary student mentoring and research dissemination. This will be achieved by running a Hot Topics Workshop at the SLMath Institute, publishing in first-rate journals, and presenting research at mathematical, engineering, and medical conferences and workshops. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-08

This EAGER project was submitted under DCL 23-109 for Clean Energy Technology topics under a NSF Clean Energy Technology Initiative. Renewable energy from ocean waves can provide about 10% of world electricity, reducing more than 3% of global CO2 production. In the United States, around 70% of the population lives along coastlines, a good wave energy resource, with limited access to other renewable energy. This research will bring together a highly collaborative and synergistic team of architects, mechanical engineers, and materials scientists to address the fundamental challenge in adopting the existing offshore renewable energy technologies: power can be generated at a competitive cost. This research will exploit a drastically new paradigm of harvesting renewable energy by creating High-Intensity Focused Ocean Waves (HIFOW). Three dimensional (3D)-printed concrete spatial shell modules will be designed and fabricated to alter the seabed topography, increase biodiversity, and harness ocean wave energy through HIFOW. The outcomes of this work will have positive societal and economic impacts through (i) the use of decarbonized concrete and (ii) the reduction of waste and low-embodied carbon by using lightweight, modular shellular structures capable of resisting extreme conditions. In addition to generating energy, the strategy used in this research can also be applied to mitigate the impact of rising water due to temperature change along many coastlines worldwide. Printing spatial shell modules made of materials compatible with coral reefs can help revive the reefs. A diverse group of students will be recruited and trained through this work to become future innovators who will develop resilient, sustainable, and equitable systems, technologies, and solutions to meet evolving societal and environmental challenges. This research connects material science, structural geometry, and additive manufacturing to renewable methods of harnessing and generating energy unique in scale, approach, and results. The design, construction, and deployment of large-scale spatial shell structures that can become a habitable place for marine life and harness wave energy have not been investigated before. Hence, this research intends to significantly improve wave energy conversion efficiency to electricity and make deploying energy-capturing devices in the ocean more effective. The performance and uses of the shell-based geometries in conjunction with fluid dynamic forces of waves in extreme conditions will open a new research horizon in designing efficient structures for extreme conditions. Using quarry-based products to make resilient material compatible with seawater will contribute to material science and construction by recycling and reusing natural materials. The ocean is a harsh environment with very complicated and highly nonlinear mathematics. The scale of any ocean wave energy prototype is immense, making conducting laboratory and field tests challenging. Hence, this research offers a drastically different approach by focusing on power generation using a single wave energy capturing (WEC) device. Potentially, this research will (1) significantly improve the efficiency of wave energy conversion to electricity, (2) vastly reduce the number, size, cost, and deployment area of WEC devices in the ocean, (3) leave more space for ocean activities, and (4) reduce interruption of marine lives and ecosystem. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-08

A common problem in mathematics is to completely classify some type of mathematical object by invariants. The field of descriptive set theory provides a general framework for studying these types of classification problems, comparing their relative difficulties, and determining when a complete classification is provably impossible. The proposed research uses these tools from descriptive set theory to understand classification problems in computability, operator algebras, topological dynamics, and ergodic theory. A key part of the project will consist of educating graduate students and other young researchers. The project has several parts. First, studying Weiss's question on amenability and hyperfiniteness using tools from Gromov's theory of asymptotic dimension. This investigation has applications to topological dynamics and operator algebras. Second, research on classical geometrical paradoxes such as the Banach-Tarski paradox and Tarski's circle squaring problem using recent advances in measurable combinatorics. Finally, the project will use Montalban's framework of true stages from computability theory to prove dichotomy theorems for definable sigma-ideals. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-08

While invisible to the eye, magnetic fields contribute to many phenomena in nature and aspects of daily life, such as ocean tides, solar flares, or electric motors. Additionally, they are used to manipulate materials for industrial applications like precision sensors, liquid-metal cooling of nuclear reactors, or magnetic drug targeting. The goal of this project is to study several mathematical models involving fluids forced by magnetic fields, and develop numerical algorithms for their simulation on a computer. This will benefit practical applications in engineering and in physical and biomedical sciences. Educational components targeting students at the high school, undergraduate and graduate level, are integrated with the research activities. The research program includes projects suitable for graduate and undergraduate research. Curriculum development for undergraduate courses in computational mathematics, and outreach to high school students in the form of an interdisciplinary math and engineering summer camp, will be undertaken. The objective of this project is the mathematical investigation of three important problems motivated from science and engineering. The first is the numerical simulation of liquid crystals subjected to magnetic fields, which are used in LCD screens. The second deals with mathematical aspects of magnetohydrodynamics turbulence in order to gain more insight into the emergence and existence of the magnetic field of the earth. The third problem concerns the question of how experimental data affects mathematical models: Probabilistic tools will be employed to develop algorithms for uncertainty quantification in compressible flows applications. These problems are described mathematically by nonlinear systems of mixed type partial differential equations (PDEs). The mathematical treatment of these systems requires the development of new analytical techniques and innovative algorithms for their simulation. The finite difference and finite volume schemes constructed in this project will be analyzed with mathematical tools such as energy estimates, compensated compactness and relative entropy methods to prove robustness and convergence. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2024 · 2024-08

Aging is ubiquitous across the tree of life, impacting biology at all levels. Among the hallmarks of aging, the accumulation of somatic mutations over time has been implicated in many leading causes of death including cancer10-12, heart disease4, and dementia5. However, most risk factors governing somatic mutation rates and patterns with age remain unknown. It has recently become possible to study the relationship between somatic mutation rates and longevity using comparative genomics. Cagan et al. (2022) demonstrated a negative correlation between somatic mutation rates and longevity, and identified conserved, longevity-associated mutational spectra across mammals. Yet, this study lacked the power to explore further due to both sparce taxonomic sampling and low sample sizes per species. Thus, there is an outstanding gap in our knowledge of how somatic mutational spectra relate to changes in longevity, and the genes involved in longevity- associated mutational spectra. To properly study the mechanisms governing mutation rates and patterns, one must sample many individuals from a group of closely-related species spanning a wide range of lifespans. My central hypothesis is that somatic mutation spectra unique to long-lived mammals are signatures of enhanced DNA damage repair responses that contribute to their extraordinary longevity. In order to identify the genetic mechanisms underlying longevity-associated somatic mutational spectra, I have generated matched skin tissue and cell lines from over 200 individuals across 10 species of a closely related (14 million years) clade of bats spanning a 3-fold range in lifespans, including the longest-lived bat species in North America. In Aim 1, to explore how somatic mutation rates co-evolve with longevity and identify longevity-associated mutational spectra in bats, I will use the highly sensitive NanoSeq to sequence 60 individuals across a trio of species in skin tissue samples. In Aim 2, using matched cell lines from the same individuals I will identify both cis and trans regulators of somatic mutation rates and spectra by using the massively parallel CRISPRi screen Repair-seq. As I transition towards an independent researcher position, in Aim 3 I will expand my functional work to other tissues and developmental contexts by developing induced pluripotent stem cells (iPSCs) from my collection of bat cell lines, and combine the cell type diversity of embryoid bodies with the power of Repair-seq to assess DNA damage repair mechanisms across all cell types simultaneously. This project is the first to explore how somatic mutation rates and spectra co-evolve with longevity both mechanistically and at high resolution. The foundations of this project will be the cornerstone of my research program exploring the evolution of longevity-associated traits in extraordinarily long-lived species using functional genomics. Using iPSCs from non-lethal skin biopsies will enable us to study aging processes in internal tissues as a part of longitudinal studies, enabling new avenues of research in the comparative biology of aging.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY / ABSTRACT The nuclear envelope (NE), a double-membrane structure surrounding the cell nucleus, and the nuclear pore complex (NPC), the largest protein assembly residing in the NE, together govern paramount cellular processes of the eukaryotic life, spanning chromatin organization, gene expression regulation, nucleocytoplasmic transport, and signal transduction. Our laboratory is committed to studying diverse and novel functions of the NE and NPC using plants as our model organisms. Our emphasis on plants stems from their unique combination of both conserved and distinct NE and NPC-associated mechanisms evolved in response to complex environmental challenges. In this proposal, we aim to leverage an integrated proteomic, molecular, genetic, and bioinformatic approach, to achieve a mechanistic understanding of how PNET1, a newly identified and evolutionarily conserved NPC membrane component, impacts mitotic progression in undifferentiated cells. Concurrently, we seek to elucidate the central role played by the NPC basket protein, GBPL3, in the precise regulation of stress-induced transcriptional reprogramming through the gene gating mechanism. This research endeavor is expected to significantly advance our understanding of fundamental biological principles underlying cell division and the regulation of gene expression occurring at the level of the NPC. Additionally, it may offer potential avenues for therapeutic interventions targeting aberrant mitotic processes in critical human diseases (e.g., cancers) and provide insights into the precise manipulation of gene expression, both in native and engineered biological systems.

NIH Research Projects · FY 2025 · 2024-08

Project Summary Large-scale changes in brain structure occur in aging and Alzheimer's Disease (AD) that demonstrate sulcal vulnerability to age-related atrophy and AD-related amyloid-β (Aβ) deposition. Recent work has shown that the morphology of tertiary sulci (the shallowest and latest-developing cortical indentations) is associated with individual differences in cognitive development and symptoms of various disorders, but these sulci have not been investigated in aging or AD. This project will investigate individual differences in gyrification in multiple brain regions in cognitively normal older adults and adults with AD, and will combine positron emission tomography (PET) and MRI imaging methods in investigating relationships between tertiary sulci, pathology, and metabolism. All sulci in medial parietal cortex (MPC) and lateral prefrontal cortex (LPFC) will be manually labeled on individual structural MRI scans of younger adults, cognitively normal older adults, and older adults with AD. Morphological metrics (such as sulcal cortical thickness) will be extracted from these labels in order to investigate their relationship to cognitive decline, AD pathology (Aβ and tau, measured with PET), and glucose metabolism (measured with PET). Aim 1 will investigate changes in sulcal morphology in MPC and LPFC in aging and AD. Aim 2 will identify how these changes in tertiary sulci relate to cognitive impairment and AD pathology. Aim 3 will determine whether sulcal morphology relates to metabolism in early adulthood and subsequent Aβ deposition in aging, as a putative explanation of how these sulci confer vulnerability to pathology and neurodegeneration. Overall, this study will investigate whether tertiary sulci can serve as structural markers of early degenerative and pathological changes relating to cognitive decline and AD. This project will provide training in (1) multimodal neuroimaging acquisition and analysis techniques, (2) statistics and data analysis methods, (3) pathophysiology of AD, (4) scientific communication, (5) teaching and mentorship skills, and (6) career development. The UC Berkeley Helen Wills Neuroscience Institute is an ideal environment for this research, ensuring access to cutting-edge PET and MRI neuroimaging facilities as well as world-class neuroimaging, biostatistics, and cognitive neuroscience experts to support the project and training goals. Ongoing collaboration with the UCSF Memory and Aging Center will provide additional training in AD pathophysiology and research. The project’s co-sponsors are exceptionally suited to support its successful completion: Dr. William Jagust is an expert in PET imaging and in applying multimodal neuroimaging techniques to understand underlying mechanisms of aging and AD, and Dr. Kevin Weiner is an expert in tertiary sulci and in linking individual differences in neuroanatomy to cognition. The proposed research and training plans will provide the applicant with the skills and support necessary to ensure successful completion of the project and a strong foundation to pursue a competitive post-doctoral fellowship and research career investigating factors underlying cognitive decline in aging and dementia.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY Over 250 million children under age 5 (43%) in low- and middle-income countries (LMIC) experience delays in development which have lasting effects on academic attainment, literacy, and economic opportunities, contributing to adverse health. Early interventions focused on responsive caregiving, early learning, and nutrition in this context have improved short-term health and development outcomes, however, whether these effects persist beyond 6 years of age is largely unknown. Further, few interventions have simultaneously targeted infectious disease prevention, another known risk factor for poor childhood development that disproportionately impacts children in LMICs. The objective of this K99/R00 proposal is to identify mechanisms through which early WASH and nutrition interventions impact health and development, assess whether these effects persist into adolescence, and estimate the potential impact of novel multicomponent interventions that target multiple prevalent risk factors in early life simultaneously. The work proposes to (1) leverage data from a large cluster randomized controlled trial in rural Bangladesh to uncover the mechanism of impact of an effective early water, sanitation, hygiene (WASH), and nutrition intervention on middle-childhood development, (2) use population intervention effects to identify early intervention targets that take into account baseline prevalence of risk and the confluence of risk factors that children experience in early life, and (3) follow up children who received the early WASH and nutrition intervention to evaluate impacts on health and development in adolescence. This work fills critical gaps in the literature regarding how early WASH and nutrition interventions work to improve outcomes, which combinations of interventions could lead to the largest improvements in child development outcomes, and the impact of early WASH and nutrition interventions on later adolescent health and development outcomes. Conducted at the University of California Berkeley, the proposed research will be guided by an exceptional mentor team with expertise spanning epidemiologic and biostatistical methods and adolescent health. The proposed plan builds on the applicant’s background in the design and evaluation of interventions in early childhood by providing subject matter training in (1) late childhood and adolescent health and development; as well as methodological training in (2) causal mediation analysis; (3) population intervention effects and target trial emulation with observational data; and (4) best practices in reproducible and transparent research. Combined, the training and research plan prepare the applicant to pursue their long-term goal of conducting research to improve health and development over the life course in low-resource global settings. Aligned with NICHD’s strategic direction to improve child and adolescent health and the transition to adulthood, this work will inform the design of future interventions that optimize the health and development through childhood and adolescence in the context of global poverty.

NSF Awards · FY 2024 · 2024-08

Most life on Earth depends on biomass and oxygen derived from photosynthetic organisms. Photosynthesis in plants and algae is performed by an organelle called the chloroplast. Inside the chloroplast, thylakoid membranes embed the photosynthetic protein complexes, which drive the light-dependent reactions of photosynthesis. Thylakoids are one of the most complex and organized membrane networks in nature. However, it is poorly understood how thylakoid membranes form and organize into their intricate architecture. In this project, the investigators have assembled an international team with a unique combination of innovative biological systems and revolutionary imaging technology to gain new insights into the fundamentals of thylakoid biogenesis in green algae. Because green algae are at the base of the green lineage on the Tree of Life, and photosynthesis and thylakoids are generally conserved, the research has broad implications for both algae and land plants. Broader impacts of this research include the intrinsic merit of understanding the fundamental biology that supports life on Earth, and the knowledge gained is likely to benefit applied projects such as improving production of crops, biofuels and bioproducts. This project provides opportunities for academic learning, including interdisciplinary training bridging cell biology, biochemistry, molecular genetics, bioinformatics, quantitative imaging, and advanced microscopy. Additional activities involve public engagement and open access of data, methods, and publications. While thylakoid membranes are central to photosynthesis, it remains unknown not only how thylakoid membranes form and organize, but also how, when, and where they are populated with photosynthetic complexes. Recently, the Roth group (Berkeley, USA) has established a rapid, controllable switch that enables cells to turn on/off photosynthesis and induce thylakoid biogenesis (a process called “greening”) in evolutionarily distant green algae. The Engel group (Basel, Switzerland) has established a cutting-edge cryo-electron tomography (cryo-ET) workflow to visualize native thylakoid membranes inside cells with the resolution to localize individual photosynthetic complexes. Combining the inducible algal systems with cryo-ET will provide an unprecedented time-resolved molecular view into the events of thylakoid biogenesis. In this project, the investigators will 1) map the stepwise events that establish thylakoid architecture and molecular organization, 2) use molecular genetics to determine and dissect roles of known thylakoid membrane remodeling proteins during thylakoid biogenesis, and 3) discover and define roles of novel candidate genes involved in thylakoid biogenesis by combining multi-omics, bioinformatics, molecular genetics, and a multidisciplinary set of analyses. The overarching goal of the collaborative research is to develop a mechanistic model of how thylakoid membranes are built, shaped into complex architecture, and precisely organized with newly assembled photosynthetic machinery. This collaborative U.S.-Swiss project is supported by the U.S. National Science Foundation (NSF) and the Swiss National Science Foundation (SNSF), where NSF funds the U.S. investigator and SNSF funds the partners in Switzerland. Funds for the US side come from the Office of International Science and Engineering, the Biological Directorate, and the Division of Molecular and Cellular Biosciences. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-08

Fluid-Structure interaction (FSI) refers to physical systems whose behavior is dictated by the interaction of an elastic body and a fluid mass. The study of FSI is relevant to various applications, ranging from aerodynamics to biomechanics. To address the inherent numerical and physical uncertainties in these applications, it is common to introduce stochastic influences into mathematical models. This project takes an initial step in investigating the effects of stochastic forces on FSI models arising in biofluidic applications that describe the interactions between a viscous fluid, such as human blood, and an elastic structure, such as a human artery. Depending on the specific application, such as the location, roughness, and size of the vessel, various mathematical models will be explored. The proposed program opens a new class of problems in mathematics involving the study of stochastic partial differential equations (PDEs) posed on randomly moving domains, particularly when the displacement of the domain boundary is not known a priori. The aim of this project is to prove that the proposed stochastic FSI problems are well-posed and to study the properties of the solutions. Education and mentoring are important components of the project, with students involved in research activities. The writing of an expository book will also be undertaken. The goal of this project is to provide existence results for a class of nonlinearly coupled stochastic FSI problems that includes a range of possibilities, such as compressible and incompressible fluid flows within thin or thick, linear or nonlinear elastic structures. Additionally, distinct coupling conditions, including the slip and no-slip kinematic coupling condition at the random and time-dependent fluid-structure interface, will be examined. Multiplicative white-in-time noise, applied both to the fluid as a volumetric body force and to the structure as an external forcing on the deformable fluid boundary, will be considered. The existence proof is based on semi-discretizing the multi-physics problem in time, decoupling the approximate problem using a penalty method, and employing an operator splitting strategy to split the fluid from the structure sub-problem(s), with the aid of a novel cut-off function approach coupled with a stopping time argument. The results of this research will shed light not only on the analytical properties of the solutions but also on the stability of the partitioned numerical schemes for stochastic FSI problems, ultimately providing insights into the robustness of these models against external noise. This study integrates tools from probability, differential geometry, and fluid dynamics. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.